yyuncong/SyncWorld-Evaluation
SyncWorld-Evaluation Evaluation sets for yyuncong/SyncWorld, a robot world model that predicts future video from past frames plus end-effector actions. Paper: SyncWorld: Visual Calibration Enables World Models as Zero-Shot SimulatorsProject page: https://umass-embodied-agi.github.io/SyncWorld/ set source tasks episodes camera views evaluation_maniskill ManiSkill 5 50 base_camera_rgb, render_camera_rgb evaluation_libero LIBERO 5 50 agentview_rgb, side_rgb Each… See the full description on the dataset page: https://huggingface.co/datasets/yyuncong/SyncWorld-Evaluation.
SyncWorld-Evaluation
Evaluation sets for `yyuncong/SyncWorld`, a robot world model that predicts future video from past frames plus end-effector actions.
Paper: SyncWorld: Visual Calibration Enables World Models as Zero-Shot Simulators Project page: https://umass-embodied-agi.github.io/SyncWorld/
Each episode is a directory holding <view>/video.mp4 plus pose.pkl, with a sibling calibration/ directory containing the per-DoF calibration sweep the model conditions on:
evaluation_maniskill/
└── PushCube-v1/
└── episode_0/
└── camera_poses_0/
├── expert/ # the episode
│ ├── render_camera_rgb/video.mp4
│ └── pose.pkl
└── calibration/ # per-DoF sweep
├── render_camera_rgb/video.mp4
└── pose.pklUsage
hf download yyuncong/SyncWorld-Evaluation --repo-type dataset --local-dir ./SyncWorld-EvaluationSee the SyncWorld README for how to run an evaluation.
Contents
Tabletop manipulation only: a robot arm, a table, and toy objects. No people appear in any frame.
License
OpenMDW-1.1, matching the SyncWorld model and the NVIDIA Cosmos-Framework it derives from. The sets are renders from ManiSkill and LIBERO; refer to those projects for their own terms.